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Cited by 242

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

Death Receptor-Ligand Systems in Cancer, Cell Death, and Inflammation

Open access
Walczak, H.·2013·Cold Spring Harbor Perspectives in Biology

Abstract

The discovery of tumor necrosis factor (TNF) marked the beginning of one of the most fascinating journeys in modern biomedical research. For the moment, this journey has culminated in the development of drugs that inhibit TNF. TNF blockers have revolutionized the treatment of many chronic inflammatory diseases. Yet, the journey seems far from over. TNF is the founding member of a family of cytokines with crucial functions in cell death, inflammation, and cancer. Some of these factors, most prominently TNF, CD95L, and TRAIL, can induce cell death. The receptors that mediate this signal are therefore referred to as death receptors, even though they also activate other signals. Here I will take you on a journey into the discovery and study of death receptor-ligand systems and how this inspired new concepts in cancer therapy and our current understanding of the interplay between cell death and inflammation.

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Crossref · 10.1101/cshperspect.a008698

Cites

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Citations

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Metadata

Authors
Walczak, H.
Venue
Cold Spring Harbor Perspectives in Biology
Published
2013-05-01
Volume
5
Issue
5
Pages
a008698-a008698
ISSN
1943-0264 (ISSN-L)
OpenAlex
W2158079918
Cited by
242
References
24
Type
posted content
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Death Receptor-Ligand Systems in Cancer, Cell Death, and Inflammation. https://app.cochat.ai/papers/10.1101/cshperspect.a008698
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Walczak, H. (2013). Death Receptor-Ligand Systems in Cancer, Cell Death, and Inflammation. Cold Spring Harbor Perspectives in Biology. https://doi.org/10.1101/cshperspect.a008698

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.